*DO FILE FOR REPLICATION OF ANALYSIS IN "CONDEMNING OR CONDONING THE PREPETRATORS? INTERNATIONAL HUMANITARIAN LAW AND ATTITUDES TOWARD WARTIME VIOLENCE"


version 14
set scheme s1mono


*CD to relevant directory


*Open data set
use "violence_rep.dta", clear




***CREATING MAIN OUTCOME VARIABLES - INDICES OF ATTITUDES TOWARD WARTIME VIOLENCE***


**OVERALL ABUSE INDEX**

*Principal factor analysis -> including both civilian and prisoner abuse component variables
factor ///
	civdiscrim3 civshelter civtransport civfood3 civvillages3 civmines ///
	prisnosave prismail pristorture prisvisit priskill prisdie
	
*Save predicted values
predict abuse
lab var abuse "Overall Abuse"

*Post-estimation commands
*Kaiser-Meyer-Olkin (KMO) measure
estat kmo
*Squared multiple correlations
estat smc
*Scree Plot
screeplot, mean

*Normalize index to range between 0 and 1
*Create temporary variable for max and min levels
egen tempt=max(abuse)
egen templ=min(abuse)
*Command below will then rescale values between 0 and 1
replace abuse = (abuse - templ)/(tempt-templ)
sum abuse
drop tempt templ

*Summary of abuse measure -> histogram with kernel density plot
	*To be used in Figure 1
histogram abuse, fraction kdensity ytitle("Proportion") ///
	title("(a) Overall Abuse Index", size(medium) position(11)) ///
	/* note("Note: Histogram of overall abuse index overlaid with kernel density plot.") */ ///
	/*options for kernel density line */ kdenop(lcolor(black)) ///
	name(abuse, replace)

*Cumulative distribution function
	*To be used in Figure 2
cumul abuse, gen(abuse_cum)
sort abuse_cum 
line abuse_cum abuse, name(abuse_cum, replace)


**CIVILIAN ABUSE INDEX**

*Principal factor analysis -> limit to civilian abuse component variables
factor civdiscrim3 civshelter civtransport civfood3 civvillages3 civmines

*Save predicted values
predict civabuse
lab var civabuse "Civilian Abuse"

*Post-estimation commands
*Kaiser-Meyer-Olkin (KMO) measure
estat kmo
*Squared multiple correlations
estat smc
*Scree Plot
screeplot, mean

*Normalize index to range between 0 and 1
*Create temporary variable for max and min levels
egen tempt=max(civabuse)
egen templ=min(civabuse)
*Command below will then rescale values between 0 and 1
replace civabuse = (civabuse - templ)/(tempt-templ)
sum civabuse
drop tempt templ

*Summary of civilian abuse measure -> histogram with kernel density plot
	*To be used in Figure 1
histogram civabuse, fraction kdensity ytitle("Proportion") ///
	title("(b) Civilian Abuse Index", size(medium) position(11)) ///
	/*options for kernel density line */ kdenop(lcolor(black)) ///
	name(civabuse, replace)

*Cumulative distribution function
	*To be used in Figure 2
cumul civabuse, gen(civabuse_cum)
sort civabuse_cum 
line civabuse_cum civabuse, name(civabuse_cum, replace)


**PRISONER ABUSE INDEX**

*Principal factor analysis -> limit to prisoner abuse component variables
factor prisnosave prismail pristorture prisvisit priskill prisdie

*Save predicted values
predict prisabuse
lab var prisabuse "Prisoner Abuse"

*Post-estimation commands
*Kaiser-Meyer-Olkin (KMO) measure
estat kmo
*Squared multiple correlations
estat smc
*Scree Plot
screeplot, mean

*Normalize index to range between 0 and 1
*Create temporary variable for max and min levels
egen tempt=max(prisabuse)
egen templ=min(prisabuse)
*Command below will then rescale values between 0 and 1
replace prisabuse = (prisabuse - templ)/(tempt-templ)
sum prisabuse
drop tempt templ

*Summary of prisoner abuse measure -> histogram with kernel density plot
	*To be used in Figure 1
histogram prisabuse, fraction kdensity ytitle("Proportion") ///
	title("(c) Prisoner Abuse Index", size(medium) position(11)) ///
	/*options for kernel density line */ kdenop(lcolor(black)) ///
	name(prisabuse, replace)

*Cumulative distribution function
	*To be used in Figure 2
cumul prisabuse, gen(prisabuse_cum)
sort prisabuse_cum 
line prisabuse_cum prisabuse, name(prisabuse_cum, replace)



**FIGURE 1. SUMMARY OF SUPPORT FOR WARTIME ABUSE INDICES**
graph combine abuse civabuse prisabuse, ycommon name(abuse_combined, replace) ///
	note("Note: Histogram for each relevant abuse index is overlaid with a kernel density plot (black line).")
graph save "abuse_combined.gph", replace


*Summary tabulations for each abuse index
tab1 abuse civabuse prisabuse
*Correlation between civilian and prisoner abuse
corr civabuse prisabuse
*Correlation between civilian and prisoner abuse at lower levels of support (less than 0.1 on either index)
corr civabuse prisabuse if civabuse<0.1 | prisabuse<0.1



**FIGURE 2. CUMULATIVE DISTRIBUTION FUNCTIONS OF SUPPORT FOR WARTIME ABUSE INDICES**
distplot line abuse civabuse prisabuse, lcolor(black gs12 black) lpattern(solid solid dash) ///
	ytitle("Cumulative Distribution") xtitle("Type of Abuse Index") ///
	legend(rows(1)) ///
	name(abuse_combined_cdf, replace)
graph save "abuse_combined_cdf.gph", replace



***EXPLANATORY VARIABLES***

*Summary tabulation for main Knowledge of Geneva Conventions variable
tab genevaknow if parallel==0
*Proportion who had heard of Geneva Conventions
tab genevaheard if parallel==0
*Proportion who correctly know purpose of the Geneva Conventions for those who had heard of them
tab genevaknow if genevaheard==1 & parallel==0


*Results related to discussion of alternative measures for knowledge of IHL in Supplementary Appendix B

*Tabulation for item on beliefs laws exist for denying civilians food
tab foodlaw
*Same for laws on attacking villages
tab villaw

*Bivariate regression model of attitudes toward denying civilians food on beliefs that relevant laws prohibiting this exist
logit foodlaw civfood3
*Similar bivariate regression model for attacking villages and beliefs on relevant laws
logit villaw civvillages3

*Correlation between these two measures and the main knowledge of Geneva Conventions measure
corr foodlaw villaw genevaknow


*Balance Test for partisan wording variable
logit partisan ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum ///
	if parallel==0

	
**Table 2. SUMMARY STATISTICS FOR MAIN VARIABLES USED IN THE ANALYSIS**
sum abuse civabuse prisabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum ///
	partisan if parallel==0


**SUPPLEMENTARY APPENDIX B TABLES B1-B11 SUMMARY STATISTICS FOR MAIN VARIABLES USED IN THE ANALYSIS, BY COUNTRY**
bys country: sum abuse civabuse prisabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum ///
	partisan if parallel==0
	
	

***ANALYSIS***

*Commands to generate Figure 3

*Overall Abuse OLS model
reg abuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Store estimates
eststo
est sto abuse
*Calculating absolute value with all variables at their median values
	margins, at((median) _all)

	
*Civilian Abuse OLS model
reg civabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Store estimates
eststo
est sto civabuse
*Calculating absolute value with all variables at their median values
	margins, at((median) _all)


*Prisoner Abuse OLS Model Measure
reg prisabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Store estimates
eststo
est sto prisabuse
*Calculating absolute value with all variables at their median values
	margins, at((median) _all)


**SUPPLEMENTARY APPENDIX C TABLE C1. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE**
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C1. Determinants of Support for Wartime Abuse") ///
	mtitles("Overall Abuse" "Civilian Abuse" "Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
eststo clear


**FIGURE 3. SUBSTANTIVE EFFECTS OF SUPPORT FOR WARTIME ABUSE**
coefplot (abuse, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	keep(genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	note("Note: Coefficient plot (OLS) indicating percentage point change in support for each" ///
	"abuse index. Lines indicate 95 percent confidence intervals. Results for partisan" ///
	"wording and country variables not shown.") ///
	graphregion(margin(large)) ///
	legend(rows(1))	///
	name(coefplot_abuse, replace)
	*Figure #: Substative Effects of Support for Wartime Abuse
graph save "coefplot_abuse.gph", replace
estimates clear



**CONDITIONAL RELATIONSHIPS**

*Commands to generate Figures 4 and 5


*CONDITIONAL ON MILITARY EXPERIENCE -> COMBATANTS VS. CIVILIANS

*Civilians
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides /*removed combatant*/ ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_civ
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides  ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_civ
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_civ
*Veterans
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto abuse_vet
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_vet
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_vet

*Example of Walt Test for Equality of "genevaknow" coefficients across subsampled models
*Run relevant subsampled models individually, though need to leave out clustered standard errors
	*Civilians
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==0 & parallel==0 /*, vce(cluster ccode)*/
	est sto civ
	*Veterans
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if combatant==1 & parallel==0 /*, vce(cluster ccode)*/		
	est sto vet
*Conduct seemingly unrelated estimation on the two saved models
	*Include clustered standard errors
suest civ vet, vce(cluster ccode)
*Wald test for "genevaknow"
test [civ_mean]genevaknow = [vet_mean]genevaknow


**SUPPLEMENTARY APPENDIX C TABLE C2. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE, BY CIVIL-MILITARY STATUS
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C2. Determinants of Support for Wartime Abuse, by Civilian-Veteran Status") ///
	mtitles("Civ-Overall Abuse" "Civ-Civilian Abuse" "Civ-Prisoner Abuse" ///
	"Vet-Overall Abuse" "Vet-Civilian Abuse" "Vet-Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear


**FIGURE 4A. BY CIVILIAN-MILITARY STATUS
coefplot ///
	/*Civilian models*/ ///
	(abuse_civ, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse_civ, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse_civ, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	bylabel(Civilians) ///
	/* Define sub-graph */ || ///
	abuse_vet civabuse_vet prisabuse_vet, ///
	/*Veteran models*/ ///
	bylabel(Veterans) ///
	/* Define overall graph options */ ||, ///
	/* Only keep main variable */ keep(genevaknow) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(rows(1) /*order(1 2 3)*/) ///
	name(coefplot_abuse_civmil, replace)
	*Figure 4a. Knowledge of Geneva Conventions and Support for Wartime Abuse, by Civilian-Veteran Status
graph save "coefplot_abuse_civmil.gph", replace
/*
Note to add manually
"Note: Plot for Knowledge of Geneva Conventions coefficient (OLS) indicating percentage point change" "in support for each abuse index by relevant subgroup. Lines indicate 95 percent confidence intervals."
*/
*Clear store model estimates from memory
estimates clear


*CONDITIONAL ON WARTIME EXPERIENCE

*Grave Wartime Experience
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==1 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_gravexp
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==1 & parallel==0, vce(cluster ccode)
	eststo
	est sto civabuse_gravexp
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==1 & parallel==0, vce(cluster ccode)
	eststo
	est sto prisabuse_gravexp
*Moderate Wartime Experience
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==1 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_modexp
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==1 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto civabuse_modexp
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==1 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto prisabuse_modexp
*Neither Type of Wartime Experience (None)
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_noexp
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto civabuse_noexp
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if expmedium3_only==0 & expmajor3==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto prisabuse_noexp


**SUPPLEMENTARY APPENDIX C TABLE C3. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE, BY WARTIME EXPERIENCE
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2 /*scalars()*/ compress nogaps label ///
	title("Table C3. Determinants of Support for Wartime Abuse, by Wartime Experience") ///
	mtitles("Severe - Overall Abuse" "Severe - Civilian Abuse" "Severe - Prisoner Abuse" ///
	"Mod - Overall Abuse" "Mod - Civilian Abuse" "Mod - Prisoner Abuse" ///
	"None - Overall Abuse" "None - Civilian Abuse" "None - Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear


**FIGURE 4B BY WARTIME EXPERIENCE
coefplot ///
	/*Grave models*/ ///
	(abuse_gravexp, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse_gravexp, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse_gravexp, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	bylabel(Severe Experience) ///
	/* Define sub-graphs */ || ///
	/*Moderate models*/ ///
	abuse_modexp civabuse_modexp prisabuse_modexp, ///
	bylabel(Moderate Experience) ///
	|| ///
	/*None models*/ ///
	abuse_noexp civabuse_noexp prisabuse_noexp, ///
	bylabel(Neither Type of Experience) ///
	/* Define overall graph options */ ||, ///
	/* Only keep main variable */ keep(genevaknow) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	byopts(ixaxes) /*show x-axis for all subgraphs*/ ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	/*Need to specify larger graph margins so labels fit*/ /*graphregion(margin(small))*/ ///
	legend(rows(1) /*order(1 2 3)*/) ///
	name(coefplot_abuse_warexp, replace)	
	*Figure 4b. Knowledge of Geneva Conventions and Support for Wartime Abuse, by Wartime Experience
graph save "coefplot_abuse_warexp.gph", replace
/*
Note to add manually
"Note: Plot for Knowledge of Geneva Conventions coefficient (OLS) indicating percentage point change" "in support for each abuse index by relevant subgroup. Lines indicate 95 percent confidence intervals."
*/
*Clear store model estimates from memory
estimates clear



*CONDITIONAL ON SUPPORTING A SIDE
tab tooksides, mis

*Did Not Take Sides
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_noside
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_noside
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_noside
*Took Sides
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==1 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_side
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_side
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 /*Removed tooksides*/ combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if tooksides==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_side

	
**SUPPLEMENTARY APPENDIX C TABLE C4. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE, BY TAKING SIDES DURING THE WAR
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2 /*scalars()*/ compress nogaps label ///
	title("Table C4. Determinants of Support for Wartime Abuse, by Taking Sides during the War") ///
	mtitles("No Side-Overall Abuse" "No Side-Civilian Abuse" "No Side-Prisoner Abuse" ///
	"Side-Overall Abuse" "Side-Civilian Abuse" "Side-Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear



**FIGURE 4C. BY TAKING SIDES DURING THE WAR
coefplot ///
	/*Did not take sides models*/ ///
	(abuse_noside, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse_noside, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse_noside, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	bylabel(Did Not Take Sides) ///
	/* Define sub-graph */ || ///
	abuse_side civabuse_side prisabuse_side, ///
	/*Took sides models*/ ///
	bylabel(Took Sides) ///
	/* Define overall graph options */ ||, ///
	/* Only keep main variable */ keep(genevaknow) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(rows(1)) ///
	name(coefplot_abuse_side, replace)
	*Figure 4c. Knowledge of Geneva Conventions and Support for Wartime Abuse, by Taking Sides during the War
graph save "coefplot_abuse_side.gph", replace
/*
Note to add manually
"Note: Plot for Knowledge of Geneva Conventions coefficient (OLS) indicating percentage point change" "in support for each abuse index by relevant subgroup. Lines indicate 95 percent confidence intervals."
*/
*Clear stored estimates
est clear



*CONDITIONAL ON GENDER
tab male, mis

*Women
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==0 & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_women
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6  /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_women
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6  /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==0 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_women
*Men
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6  /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto abuse_men
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6  /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_men
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6  /* Removed male */ educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if male==1 & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_men


**SUPPLEMENTARY APPENDIX C TABLE C5. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE, BY GENDER
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2 /*scalars()*/ compress nogaps label ///
	title("Table C5. Determinants of Support for Wartime Abuse, by Gender") ///
	mtitles("Women-Overall Abuse" "Women-Civilian Abuse" "Women-Prisoner Abuse" ///
	"Men-Overall Abuse" "Men-Civilian Abuse" "Men-Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear

*FIGURE 4D BY GENDER
coefplot ///
	/*Female models*/ ///
	(abuse_women, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse_women, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse_women, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	bylabel(Women) ///
	/* Define sub-graph */ || ///
	/*Male models*/ ///
	abuse_men civabuse_men prisabuse_men, ///
	bylabel(Men) ///
	/* Define overall graph options */ ||, ///
	/* Only keep main variable */ keep(genevaknow) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(rows(1)) ///
	name(coefplot_abuse_gender, replace)
	*Figure 4d. Knowledge of Geneva Conventions and Support for Wartime Abuse, by Gender
graph save "coefplot_abuse_gender.gph", replace
/*
Note to add manually
"Note: Plot for Knowledge of Geneva Conventions coefficient (OLS) indicating percentage point change" "in support for each abuse index by relevant subgroup. Lines indicate 95 percent confidence intervals."
*/
*Clear stored estimates
est clear



*CONDITIONAL ON EDUCATION
tab educatq_war, mis

*Upper 2 Quartiles
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==3 | educatq_war==4) & parallel==0, vce(cluster ccode)
	eststo
	est sto abuse_edhigh
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==3 | educatq_war==4) & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_edhigh
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==3 | educatq_war==4) & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_edhigh
*Lower 2 Quartiles
	*Overall Abuse
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==1 | educatq_war==2) & parallel==0, vce(cluster ccode)		
	eststo
	est sto abuse_edlow
	*Civilian Abuse
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==1 | educatq_war==2) & parallel==0, vce(cluster ccode)		
	eststo
	est sto civabuse_edlow
	*Prisoner Abuse
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male /*Removed educatq_war*/ kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if (educatq_war==1 | educatq_war==2) & parallel==0, vce(cluster ccode)		
	eststo
	est sto prisabuse_edlow


**SUPPLEMENTARY APPENDIX C TABLE C6. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE, BY LEVEL OF EDUCATION**
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C6 Determinants of Support for Wartime Abuse, by Level of Education") ///
	mtitles("Highed-Overall Abuse" "Highed-Civilian Abuse" "Highed-Prisoner Abuse" ///
	"Lowed-Overall Abuse" "Lowed-Civilian Abuse" "Lowed-Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear


**FIGURE 5. KNOWLEDGE OF GENEVA CONVENTIONS AND SUPPORT FOR WARTIME ABUSE, BY LEVEL OF EDUCATION
coefplot ///
	/*Upper two quartiles models*/ ///
	(abuse_edhigh, label("Overall Abuse") mcolor(black) ciopts(lcolor(black))) ///
	(civabuse_edhigh, label("Civilian Abuse") mcolor(gs12) ciopts(lcolor(gs12))) ///
	(prisabuse_edhigh, label("Prisoner Abuse") mcolor(gs8) ciopts(lcolor(gs8))), ///
	bylabel(Upper Two Quartiles) ///
	/* Define sub-graph */ || ///
	/*Lower two quartiles models*/ ///
	abuse_edlow civabuse_edlow prisabuse_edlow, ///
	bylabel(Lower Two Quartiles) ///
	/* Define overall graph options */ ||, ///
	/* Only keep main variable */ keep(genevaknow) ///
	xline(0) xtitle(Percentage Change in Outcome) ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(rows(1)) ///
	name(coefplot_abuse_educ, replace)
	*Figure 5. Knowledge of Geneva Conventions and Support for Wartime Abuse, by Level of Education
graph save "coefplot_abuse_educ.gph", replace
/*
Note to add manually
"Note: Plot for Knowledge of Geneva Conventions coefficient (OLS) indicating percentage point change" "in support for each abuse index by relevant subgroup. Lines indicate 95 percent confidence intervals."
*/
*Clear stored estimates
est clear



***MODELS RELATED TO MECHANISMS***

*Commands to generate Figures 6 through 8


**MODELS FOR FIGURE 6 ON BASIS OF RULES FOR WHICH VIOLATORS SHOULD BE HELD ACCOUNTABLE**

*Model for a prior item on whether believe respondents should be held accountable in the first place
logit punish ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)

*Main model for basis of rules for which violators should be held accountable
*Multinomial logit with single indicator (baseline outcome is religious values)
mlogit baserules2 ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 & whynot_moral==1 /* [pweight=weights]*/, vce(cluster ccode) ///
	b(3)
eststo
margins, dydx(*) at((median) _all) post
est sto baserules2


**SUPPLEMENTARY APPENDIX C TABLE C7. DETERMINANTS OF BELIEFS OVER THE BASIS OF RULES FOR WHICH VIOLATORS SHOULD BE HELD ACCOUNTABLE**
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	pr2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C7. Determinants of Beliefs over the Basis of Rules for which Violators Should be Held Accountable") ///
	mtitles("International Law" "Domestic Law" "Religious Values" "Other Values") ///
	nonotes addnotes("Note: Multinomial logit estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear
estimates clear

**FIGURE 6. KNOWLEDGE OF GENEVA CONVENTIONS AND BELIEFS ON THE BASIS OF RULES FOR WHICH VIOLATORS SHOULD BE HELD ACCOUNTABLE
*Note: to generate this figure, results from the -margins- command after the -mlogit- model above were
	*saved to a separate data set
stop

/*
*Use the following data set and commands to generate Figure 6
use "baserules.dta", clear

twoway ///
	(rspike lowerci upperci group, lcolor(black) horizontal) ///
	(scatter group value, msymbol(circle) mcolor(black) /*msize(medlarge)*/), ///
	xscale(range (-0.15 0.15)) xlabel(-0.15(0.05)0.15, nogrid) ///
	yscale(range (0 5)) ///
	xline(0, lcolor(black)) ///
	xtitle("Percentage Change in Predicted" "Probability of Outcome") ///
	ytitle("") ///
	legend(off) ///
	scheme(s1mono) ///
	/* ylabel(, grid) */ ///
	ylabel(1 "Other Values" 2 "Religious Values" 3 "Domestic Law" 4 "International Law", angle(0) nogrid) ///
	note("Note: Multinomial logit estimation. Average marginal effect (percentage point change in the" ///
	"predicted probability of the outcome) of Knowledge of Geneva Conventions, holding all other" ///
	"variables at their median values. Lines indicate 95 percent confidence intervals. Model is limited" ///
	"to respondents who believed there were rules for which people should be held accountable if they" ///
	"violated them.") ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	name(coefplot_baserules, replace)
	/*Figure #:Knowledge of the Geneva Conventions and Beliefs on the Basis of Rules for Which Violators /// 
		Should be Held Accountable*/
graph save "coefplot_baserules.gph", replace
*/



**MODELS FOR FIGURE 7 ON BELIEFS FOR LIMITS ON WARTIME CONDUCT**

*Warlimits model
logit warlimits ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto warlimits
*Note some separation problemswhere some country variables predict binary outcome perfectly.
	*Afghanistan, Bosnia, Georgia, Israel
*Re-estimate using penalized-likelihood model 
	*Does not allow clustered standard errors
/*
firthlogit warlimits ///
	genevaknow warlive2 /*warmove2*/ expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 /* [pweight=weights]*/ /*, vce(cluster ccode)*/
*/

*Reason for limits ->  because morally wrong (vs. causes too many problems)
	*Limit to those who said there *were* limits on conduct
logit whynot_moral ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 /* [pweight=weights]*/, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto whynot_moral


**SUPPLEMENTARY APPENDIX C TABLE C8. DETERMINANTS OF BELIEFS IN LIMITS ON WARTIME CONDUCT**
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	pr2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C8. Determinants of Beliefs in Limits on Wartime Conduct") ///
	mtitles("Limits on Fighting Exist" "Limits b/c Morally Wrong (vs. Instrumental)") ///
	nonotes addnotes("Note: Logit estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear



**FIGURE 7. KNOWLEDGE OF GENEVA CONVENTIONS AND BELIEFS OF LIMITS ON WARTIME CONDUCT**
coefplot ///
	(warlimits, label(Limits on Fighting Exist)	mcolor(black) ciopts(lcolor(black))) ///
	(whynot_moral, label("Limits b/c Morally Wrong" "(vs. Instrumental)") mcolor(gs12) ciopts(lcolor(gs12))), ///
	keep(genevaknow) ///
	xline(0) xscale(range(-0.2 0.2)) xlabel(-0.2(0.05)0.2) xtitle("Percentage Change in Predicted" "Probability of Outcome") ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	note("Note: Logit estimation separately for each outcome. Average marginal effect (percentage point" ///
	"change in the predicted probability of the outcome) of Knowledge of Geneva Conventions, while" ///
	"holding all other variables at their median values. Lines indicate 95 percent confidence intervals." ///
	"Model for 'Why Limits?' limited to respondents who answered affirmatively to prior question on" /// 
	" 'Any Limits on Fighting?' ") ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(rows(1)) ///
	name(coefplot_limits, replace)
	*Figure 7. Knowledge of Geneva Conventions and Beliefs of Limits on Wartime Conduct
graph save "coefplot_limits.gph", replace
est clear



**MODELS FOR FIGURE 8 FOR BELIEFS ON WHY BREAKING LIMITS ON WARTIME CONDUCT IS WRONG

*Use separate logit models because respondents allowed to give two choices to original question
	*on which these variables are based.
*Limited to those who said limits were because it was "morally wrong" (See earlier models for Figure 7)

*Against the Law/Human Rights
logit wronglawhr ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 & whynot_moral==1, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto wronglawhr

*Religion
	*May be because of religiosity
logit wrongrel ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 & whynot_moral==1 /* [pweight=weights]*/, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto wrongrel

*Culture (and people)
logit wrongcult2 ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 & whynot_moral==1 /* [pweight=weights]*/, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto wrongcult2

*Personal Code
logit wrongcode ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0 & warlimits==1 & whynot_moral==1 /* [pweight=weights]*/, vce(cluster ccode)
eststo
margins, dydx(*) at((median) _all) post
est sto wrongcode


**SUPPLEMENTARY APPENDIX C TABLE C9 DETERMINANTS OF BELIEFS FOR WHY BREAKING LIMITS ON WARTIME CONDUCT IS WRONG**
esttab using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	pr2(a2) /*scalars()*/ compress nogaps label ///
	title("Table C10. Determinants of Beliefs for Why Breaking Limits on Wartime Conduct is Wrong") ///
	mtitles("Law/Human Rights" "Religion" "Culture" "Personal Code") ///
	nonotes addnotes("Note: Logit estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown.")
*Clear stored estimates
eststo clear

**FIGURE 8. KNOWLEDGE OF GENEVA CONVENTIONS AND BELIEFS FOR WHY BREAKING LIMITS ON WARTIME CONDUCT IS WRONG
coefplot ///
	(wronglawhr, label(Law/Human Rights) mcolor(black) ciopts(lcolor(black))) ///
	(wrongrel, label(Religion) mcolor(gs12) ciopts(lcolor(gs12))) ///
	(wrongcult2, label(Culture) mcolor(gs8) ciopts(lcolor(gs8))) ///
	(wrongcode, label(Personal Code) mcolor(black) ciopts(lcolor(black) /*lpattern(dash)*/)), ///
	keep(genevaknow) ///
	xline(0) xtitle("Percentage Change in Predicted" "Probability of Outcome") ///
	/*remove ylabel and ticks*/ ylabel(none) ///
	note("Note: Logit estimation separately for each outcome. Average marginal effect (percentage point" ///
	"change in the predicted probability of the outcome) of Knowledge of Geneva Conventions, while" ///
	"holding all other variables at their median values. Lines indicate 95 percent confidence intervals." ///
	"Models limited to respondents who answered 'It's wrong' on previous item of 'Why are there limits" ///
	"on fighting?' ") ///
	/*Need to specify larger graph margins so labels fit*/ graphregion(margin(large)) ///
	legend(title("Against...", size(medsmall) /*position(11)*/)) ///
	name(coefplot_whywrong, replace)
	*Figure 8. Knowledge of Geneva Conventions and Beliefs of Why Breaking Limits on Wartime Conduct is Wrong
graph save "coefplot_whywrong.gph", replace
est clear




**VARIOUS ROBUSTNESS CHECKS FOR MAIN REGRESSION MODELS**


/*
**DEALING WITH MISSING DATA -> RE-ESTIMATING USING MULTIPLE IMPUTATION**

*Run all existing commands up to this point in the replication do file to create relevant summary measures

*Format and set data for imputation
mi set mlong
*Register variables (allow all to be imputed)
mi register imputed abuse civabuse prisabuse genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum
	*Except the partisan treatment variable
	mi register imputed partisan
*Conduct multiple imputation on all variables (create 5 - using multivariate normal regression method
mi impute mvn abuse civabuse prisabuse genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum ///
	partisan ///
	, ///
	add(5) rseed(97196)
*Summarize new data
sum abuse civabuse prisabuse genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan
sum abuse civabuse prisabuse genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	if _mi_m==0
*Multivariate normal regression method assumes continuous values, but many variables are categorical, so recode accordingly
*Following variables are binary
	*genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant male kidsdum
replace genevaknow = 0 if genevaknow<0.5 & _mi_m>0
	replace genevaknow = 1 if genevaknow>=0.5 & _mi_m>0
replace warlive2 = 0 if warlive2<0.5 & _mi_m>0
	replace warlive2 = 1 if warlive2>=0.5 & _mi_m>0
replace expmedium3_only = 0 if expmedium3_only<0.5 & _mi_m>0
	replace expmedium3_only = 1 if expmedium3_only>=0.5 & _mi_m>0
replace expmajor3 = 0 if expmajor3<0.5 & _mi_m>0
	replace expmajor3 = 1 if expmajor3>=0.5 & _mi_m>0
replace tooksides = 0 if tooksides<0.5 & _mi_m>0
	replace tooksides = 1 if tooksides>=0.5 & _mi_m>0
replace combatant = 0 if combatant<0.5 & _mi_m>0
	replace combatant = 1 if combatant>=0.5 & _mi_m>0
replace male = 0 if male<0.5 & _mi_m>0
	replace male = 1 if male>=0.5 & _mi_m>0
replace kidsdum = 0 if kidsdum<0.5 & _mi_m>0
	replace kidsdum = 1 if kidsdum>=0.5 & _mi_m>0
*agecat6 is 6 categories
replace agecat6 = 1 if agecat6<1.5 & _mi_m>0
	replace agecat6 = 2 if agecat6>=1.5 & agecat6<2.5 & _mi_m>0
	replace agecat6 = 3 if agecat6>=2.5 & agecat6<3.5 & _mi_m>0
	replace agecat6 = 4 if agecat6>=3.5 & agecat6<4.5 & _mi_m>0
	replace agecat6 = 5 if agecat6>=4.5 & agecat6<5.5 & _mi_m>0
	replace agecat6 = 6 if agecat6>=5.5 & agecat6!=.  & _mi_m>0
*educatq_war if 4 categories
replace educatq_war = 1 if educatq_war<1.5 & _mi_m>0
	replace educatq_war = 2 if educatq_war>=1.5 & educatq_war<2.5 & _mi_m>0
	replace educatq_war = 3 if educatq_war>=2.5 & educatq_war<3.5 & _mi_m>0
	replace educatq_war = 4 if educatq_war>=3.5 & educatq_war!=. & _mi_m>0
sum abuse civabuse prisabuse genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan

*Re-estimate main abuse index models using imputed data
*Overall abuse
mi estimate, post /*to save results*/: reg abuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
eststo abuse
est sto abuse
*Civilian abuse
mi estimate, post /*to save results*/: reg civabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
eststo civabuse
est sto civabuse
*Prisoner abuse
mi estimate, post /*to save results*/: reg prisabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
eststo prisabuse
est sto prisabuse

**SUPPLEMENTARY APPENDIX C TABLE C10. DETERMINANTS OF SUPPORT FOR WARTIME ABUSE (MULTIPLE IMPUTATION OF MISSING VALUES)
esttab abuse civabuse prisabuse using table1, csv replace b(a2) se(a2) star (+ 0.1 * 0.05 ** 0.01) ///
	r2(a2) compress nogaps label ///
	title("Table C10. Determinants of Support for Wartime Abuse (Multiple Imputation of Missing Values)") ///
	mtitles("Overall Abuse" "Civilian Abuse" "Prisoner Abuse") ///
	nonotes addnotes("Note: OLS estimation. Robust standard errors in parentheses (clustered by country)." ///
	"+ p<.1; * p<.05; ** p<.01." "Coefficients for partisan wording and country variables not shown." ///
	"Multiple imputation of missing values using multivariate normal regression estimator.")
*Clear stored estimates
eststo clear

*/



*MATCHING*

/*
*GENETIC MATCHING
*Main matching analysis described in the text used a genetic matching routine 
*This analysis was conducted using the "Matching" package in R
*The commands for the genetic matching analysis are included below, but need to be conducted in R
*Specific versions of the data sets were generated to operate properly with the "Matching" package
	*These are "abuse_match.dta" , "civabuse_match.dta" and "prisabuse_match.dta" 

#Overall Abuse Genetic Matching Analysis
#Initial set-up
load package MASS
library(foreign)
library(Matching)
library(rbounds)
rm(list=ls(all=TRUE))

#Define relevant filepath for file location
#Attach version of data set for overall abuse matching analysis
In.abuse<-read.dta(file="abuse_match.dta", convert.factors = FALSE)
attach(In.abuse)
summary(In.abuse)

#Identify covariates for matching
X <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Identify covariates to balance on
BalanceMat <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Call GenMatch to find optimal weights for obtaining balance on covariates
genout <- GenMatch(Tr=genevaknow, X=X, BalanceMatrix=BalanceMat, estimand="ATE", M=1, data.type.int=FALSE)

#Call estimated effect of Knowledge of Geneva Conventions on Overall Abuse Measure
mout <- Match(Y=abuse, Tr=genevaknow, X=X, estimand="ATE", Weight.matrix=genout, M=1)      
summary(mout)
	#ATT
	mout <- Match(Y=abuse, Tr=genevaknow, X=X, estimand="ATT", Weight.matrix=genout, M=1)      
	summary(mout)
#Perform Rosenbaum sensitivity analysis using "rbounds" package
psens(mout, Gamma=2.5, GammaInc=.1)


#Civilian Abuse Genetic Matching Analysis
#Initial set-up
load package MASS
library(foreign)
library(Matching)
library(rbounds)
rm(list=ls(all=TRUE))

#Define relevant filepath for file location
#Attach version of data set for civilian abuse matching analysis
In.civabuse<-read.dta(file="civabuse_match.dta", convert.factors = FALSE)
attach(In.civabuse)
summary(In.civabuse)

#Identify covariates for matching
X <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Identify covariates to balance on
BalanceMat <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Call GenMatch to find optimal weights for obtaining balance on covariates
genout <- GenMatch(Tr=genevaknow, X=X, BalanceMatrix=BalanceMat, estimand="ATE", M=1, data.type.int=FALSE)

#Call estimated effect of Knowledge of Geneva Conventions on Civilian Abuse Measure
mout <- Match(Y=civabuse, Tr=genevaknow, X=X, estimand="ATE", Weight.matrix=genout, M=1)      
summary(mout)
	#ATT
	mout <- Match(Y=civabuse, Tr=genevaknow, X=X, estimand="ATT", Weight.matrix=genout, M=1)      
	summary(mout)
#Perform Rosenbaum sensitivity analysis using "rbounds" package
psens(mout, Gamma=1.5, GammaInc=.1)


#Prisoner Abuse Genetic Matching Analysis
#Initial set-up
load package MASS
library(foreign)
library(Matching)
library(rbounds)
rm(list=ls(all=TRUE))

#Define relevant filepath for file location
#Attach version of data set for prisoner abuse matching analysis
In.prisabuse<-read.dta(file="prisabuse_match.dta", convert.factors = FALSE)
attach(In.prisabuse)
summary(In.prisabuse)

#Identify covariates for matching
X <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Identify covariates to balance on
BalanceMat <- cbind(warlive2, expmedium3_only, expmajor3, tooksides, combatant, agecat6, male, educatq_war, kidsdum, partisan, afghanistan, bosnia, cambodia, elsalvador, georgia, israel, lebanon, nigeria, philippines, somalia)

#Call GenMatch to find optimal weights for obtaining balance on covariates
genout <- GenMatch(Tr=genevaknow, X=X, BalanceMatrix=BalanceMat, estimand="ATE", M=1, data.type.int=FALSE)

#Call estimated effect of Knowledge of Geneva Conventions on Prisoner Abuse Measure
mout <- Match(Y=prisabuse, Tr=genevaknow, X=X, estimand="ATE", Weight.matrix=genout, M=1)      
summary(mout)
	#ATT for Treated
	mout <- Match(Y=prisabuse, Tr=genevaknow, X=X, estimand="ATT", Weight.matrix=genout, M=1)      
	summary(mout)
#Perform Rosenbaum sensitivity analysis using "rbounds" package
psens(mout, Gamma=2.5, GammaInc=.1)
 
*/


*Alternative Matching Routine
*Using nearest-neighbor matching (based on Mahalanobis distance)
*Can be estimated using main Stata data set generated through prior commands in this do file

*Overall Abuse
teffects nnmatch ///
	( ///
	/*DV*/ abuse ///
	/*covariates*/ warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
	) ///
	/*treatment*/ (genevaknow) ///
	if parallel==0 ///
	, ///
	/*exact match on country*/ ///
	ematch(afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia) ///
	/*number of matches*/ nneighbor(1)

*Civilian Abuse
teffects nnmatch ///
	( ///
	/*DV*/ civabuse ///
	/*covariates*/ warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
	) ///
	/*treatment*/ (genevaknow) ///
	if parallel==0 ///
	, ///
	/*exact match on country*/ ///
	ematch(afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia) ///
	/*number of matches*/ nneighbor(1)
	
*Prisoner Abuse
teffects nnmatch ///
	( ///
	/*DV*/ prisabuse ///
	/*covariates*/ warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
	) ///
	/*treatment*/ (genevaknow) ///
	if parallel==0 ///
	, ///
	/*exact match on country*/ ///
	ematch(afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia) ///
	/*number of matches*/ nneighbor(1)




*EXCLUDING INDIVIDUAL COUNTRIES FROM MAIN MODEL, ONE-BY-ONE
*Overall Abuse	
	*Without Afghanistan
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if afghanistan!=1 & parallel==0, vce(cluster ccode)
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if bosnia!=1 & parallel==0, vce(cluster ccode)
	*Without Cambodia
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if cambodia!=1 & parallel==0, vce(cluster ccode)
	*Without El Salvador
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if elsalvador!=1 & parallel==0, vce(cluster ccode)
	*Without Georgia
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if georgia!=1 & parallel==0, vce(cluster ccode)
	*Without Israel
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if israel!=1 & parallel==0, vce(cluster ccode)
	*Without Lebanon
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if lebanon!=1 & parallel==0, vce(cluster ccode)
	*Without Nigeria
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if nigeria!=1 & parallel==0, vce(cluster ccode)
	*Without Philippines
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if philippines!=1 & parallel==0, vce(cluster ccode)
	*Without Somalia
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if somalia!=1 & parallel==0, vce(cluster ccode)
	*Without South Africa
	reg abuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if southafrica!=1 & parallel==0, vce(cluster ccode)

*Civilian Abuse	
	*Without Afghanistan
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if afghanistan!=1 & parallel==0, vce(cluster ccode)
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if bosnia!=1 & parallel==0, vce(cluster ccode)
	*Without Cambodia
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if cambodia!=1 & parallel==0, vce(cluster ccode)
	*Without El Salvador
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if elsalvador!=1 & parallel==0, vce(cluster ccode)
	*Without Georgia
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if georgia!=1 & parallel==0, vce(cluster ccode)
	*Without Israel
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if israel!=1 & parallel==0, vce(cluster ccode)
	*Without Lebanon
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if lebanon!=1 & parallel==0, vce(cluster ccode)
	*Without Nigeria
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if nigeria!=1 & parallel==0, vce(cluster ccode)
	*Without Philippines
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if philippines!=1 & parallel==0, vce(cluster ccode)
	*Without Somalia
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if somalia!=1 & parallel==0, vce(cluster ccode)
	*Without South Africa
	reg civabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if southafrica!=1 & parallel==0, vce(cluster ccode)

*Prisoner Abuse	
	*Without Afghanistan
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if afghanistan!=1 & parallel==0, vce(cluster ccode)
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if bosnia!=1 & parallel==0, vce(cluster ccode)
	*Without Cambodia
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if cambodia!=1 & parallel==0, vce(cluster ccode)
	*Without El Salvador
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if elsalvador!=1 & parallel==0, vce(cluster ccode)
	*Without Georgia
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if georgia!=1 & parallel==0, vce(cluster ccode)
	*Without Israel
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if israel!=1 & parallel==0, vce(cluster ccode)
	*Without Lebanon
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if lebanon!=1 & parallel==0, vce(cluster ccode)
	*Without Nigeria
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if nigeria!=1 & parallel==0, vce(cluster ccode)
	*Without Philippines
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if philippines!=1 & parallel==0, vce(cluster ccode)
	*Without Somalia
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if somalia!=1 & parallel==0, vce(cluster ccode)
	*Without South Africa
	reg prisabuse ///
		genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
		agecat6 male educatq_war kidsdum partisan ///
		afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
		if southafrica!=1 & parallel==0, vce(cluster ccode)

	

*INCLUDING AN INDICATOR FOR "MARRIED" RESPONDENTS IN MAIN MODELS
	*This is in addition to the variable for having children "kidsdum" in the original models
*Overall
reg abuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum /*added*/ married partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Civilian
reg civabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum /*added*/ married partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Prisoner
reg prisabuse ///
	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum /*added*/ married partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)

	

*SUBSTITUTING ALTERNATIVE EDUCATION VARIABLE (YEARS OF EDUCATION) IN MAIN MODELS
*Overall
reg abuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male  /*diff var*/ educ kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Civilian
reg civabuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male  /*diff var*/ educ kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)
*Prisoner
reg prisabuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male  /*diff var*/ educ kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if parallel==0, vce(cluster ccode)



*SUBSTITUTING PARALLEL STUDIES CONDUCTED IN THE PHILIPPINES AND BOSNIA  IN MAIN MODELS
*Overall
reg abuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if nopar==1 | parallel==1, vce(cluster ccode)
*Civilian
reg civabuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if nopar==1 | parallel==1, vce(cluster ccode)
*Prisoner
reg prisabuse ///
 	genevaknow warlive2 expmedium3_only expmajor3 tooksides combatant ///
	agecat6 male educatq_war kidsdum partisan ///
	afghanistan bosnia cambodia elsalvador georgia israel lebanon nigeria philippines somalia ///
	if nopar==1 | parallel==1, vce(cluster ccode)


	
*END OF REPLICATION DO FILE
stop








